Collaborative Research: Worker Cross-Training and Assignment Considering Learning/Forgetting Effects

这个建议模型的工作轮换的影响，在学习和遗忘方面，对一组工人的整体生产力。这揭示了工人灵活性与潜在的效率降低之间的交叉培训权衡。该研究将实验心理学（学习和遗忘曲线）与强大的数学规划和优化方法相结合，开发出对管理者有重要意义的工具。这三个研究问题将在计算机模拟的帮助下得到回答，并在现场进行验证。广泛的影响是提高生产力和改善工作环境的潜力，这将有利于经济。现代制造实践通常使用单元设计和即时操作，可能会破坏持续学习过程。在过去，管理人员依靠长期生产的专业化来提高生产率，而今天，他们经常利用交叉培训来管理快速变化的技术和不确定的需求。然而，目前还没有具体的指导方针来帮助管理人员决定交叉培训、任务轮换和工作排序的水平。本研究的目的是提高生产力的组织与工作轮换，通过分配和调度的工人的任务，并检查首选的分配和交叉培训水平，在这种环境下。根据个人学习和遗忘的特点，工人被分配和安排任务的方式，旨在最大限度地提高生产力。该项目的一个重要贡献是了解由于专业化程度降低而导致的生产力损失与由于交叉培训而带来的灵活性收益之间的权衡。该研究将解决以下研究问题：1。在一个工作组中，对于三个目标a，n个工作者中的每一个应该被分配到m个任务中的哪一个。在给定n个工作者B的情况下，最大化吞吐量。）最大限度地减少给定生产要求所需的工人数量，c.）最小化n个工人满足给定生产要求所需的时间。2.应允许或要求何种程度的交叉培训，包括：a.）除了最初的任务分配，n个工人还应该负责多少任务？B.）工人应该多久和以什么模式在这些交叉训练的任务之间转换（即，时间表是什么）？3.环境因素的影响是什么，包括工作场所设计的影响（即，工作和/或信息流的模式），相邻与非相邻的工作者任务分配（即，旅游旅行时间成本）、单个产品与多个产品以及批量大小。首先，研究人员将开发基于数学编程的决策模型，用于分配和调度工人的任务。这些模型将纳入个体工人学习和遗忘的影响。其次，研究人员将开发一个测量模型，用于量化工人的学习和遗忘，以用于数学编程模型。第三，研究者将根据个体工人的学习和遗忘模式的经验分布，首先通过模拟，然后将结果应用于真实的工作环境，来检查上述研究问题。这项研究的影响可能是广泛的，直接影响到许多服务和制造业组织，利用交叉培训。此外，拟议的研究将量化与交叉训练计划相关的学习和遗忘效应的成本。虽然有很好的理由交叉培训工人，许多与增加灵活性有关，但当这些工人学习新任务时，他们容易忘记其他人，生产力可能会受到显着影响。因此，这项研究将提供描述性和规范性的能力，为组织量化和计划交叉培训计划在制造和服务环境。

This proposal models the effects of job rotation, in terms of learning and forgetting, on the overall productivity of a group of workers. This reveals the cross-training tradeoff between worker flexibility versus potentially reduced efficiency. The research combines experimental psychology (leaning and forgetting curves) with robust mathematical programming and optimization methods to develop tools that could be of significant use to managers. The three research questions will be answered with the aid of computer simulation and validated in the field. The broad impact is the potential for enhancing productivity and improvements in the work environment that will benefit the economy. Modern manufacturing practices, which often use cellular designs and just-in-time operations, may disrupt the continuous learning process. While in the past managers relied on specialization over long production runs to improve productivity, today they often make use of cross training in an attempt to manage rapidly changing technology and uncertain demand. However, at present, no concrete guidelines exist to aid managers in deciding levels of cross training, task rotation, and the sequencing of jobs. The objective of this research is to improve productivity in organizations with job rotation through assignment and scheduling of workers to tasks and to examine preferred assignment and cross training levels in this environment. Based on individual learning and forgetting characteristics, workers are assigned and scheduled to tasks in ways designed to maximize productivity. An important contribution of the project is understanding the tradeoffs between lost productivity due to reduced specialization and the flexibility benefits due to cross training. The study will address the following research questions: 1. Within a work group, to which of m tasks should each of n workers be assigned for three objectives a.) Maximize throughput given n workers, b.) Minimize the number of workers needed for a given production requirement, c.) Minimize the time required for n workers to meet a given production requirement. 2. What degree of cross training should be allowed or required, including: a.) How many tasks in addition to the initial assignment should the n workers be responsible for? b.) How often and in what pattern should workers shift between these cross trained tasks (i.e., what is the schedule)? 3. What are the effects of environmental factors including, Workplace design implications (i.e., pattern of work and/or information flow), Adjacent vs. non-adjacent worker-task assignments (i.e., tour travel time costs), Single vs. multiple products, and Batch size. First, the investigators will develop math programming based decision models for assigning and scheduling workers to tasks. The models will incorporate the effects of individual worker learning and forgetting. Second, the investigators will develop a measurement model for quantifying worker learning and forgetting for use in the math programming models. Third, the investigators will examine the research questions described above based on empirical distributions of individual workers' learning and forgetting patterns, through simulation first and then subsequently applying the results in real work settings. The impact of this research is potentially broad, affecting directly the many service and manufacturing organizations that make use of cross training. Further, the proposed research will quantify the costs from learning and forgetting effects that are associated with cross training programs. While there are good reasons for cross training workers, many related to increased flexibility, when these workers are learning new tasks they are subject to forgetting others and productivity may suffer significantly. Thus, the research will provide both descriptive and prescriptive capabilities for organizations to quantify and plan cross training programs in manufacturing and service settings.